This research investigates the adequacy of a remote sensing instrument's spatial resolution for monitoring crop growth over agricultural landscapes with different spatial patterns. The approach is based on the postulate that time series of a subset of pixels can characterize crop growth over a small zone with similar agro-climatic growing conditions. The point spread function (PSF) is explicitly taken into account in order to identify, at different scales, the pixels whose effective instantaneous field of view (EIFOV) falls within the larger fields of the target crop. This pixel sampling approach enables the resolution to be much coarser than what would be recommended by the predominant scale of spatial variation of the image. Since monitoring crop growth is often done to evaluate the total regional crop production, the method is extended to explore the resolution necessary for crop area estimation.